Visitor relationship orientation of destination marketing organisations. Pike, S., Murdy, S. & Lings, ..... This is clearly more than an e-newsletter emailed to all ...
This is the author’s version of a work that was submitted/accepted for publication in the following source: Pike, Steven D., Murdy, Samantha, & Lings, Ian (2011) Visitor relationship orientation of destination marketing organisations. Journal of Travel Research, 50(4), pp. 443-453. This file was downloaded from: http://eprints.qut.edu.au/42213/
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Visitor relationship orientation of destination marketing organisations Pike, S., Murdy, S. & Lings, I. (2011). Visitor relationship orientation of destination marketing organisations. Journal of Travel Research. 50(4): 443-453. Abstract The proposition underpinning this study is engaging in meaningful dialogue with previous visitors represents an efficient and effective use of resources for a destination marketing organization (DMO), compared to above the line advertising in broadcast media. However there has been a lack of attention in the tourism literature relating to destination switching, loyalty and customer relationship management (CRM) to test such a proposition. This paper reports an investigation of visitor relationship marketing (VRM) orientation among DMOs. A model of CRM orientation, which was developed from the wider marketing literature and a prior qualitative study, was used to develop a scale to operationalise DMO visitor relationship orientation. Due to a small sample, the Partial Least Squares (PLS) method of structural equation modelling was used to analyse the data. Although the sample limits the ability to generalise, the results indicated the DMOs’ visitor orientation is generally responsive and reactive rather than proactive.
Key words Tourism marketing, CRM, destination marketing, repeat visitors, destination loyalty, visitor relationship marketing (VRM)
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Introduction In today’s competitive tourism markets the consumer-traveller is spoilt by choice of available destinations, and so it is likely many places are substitutable in decision making (Pike, 2008). In response to increasing competition, destinations have progressively become involved in place branding development since the 1990s (Morgan, Pritchard & Pride, 2002). Successfully differentiating a destination brand in markets crowded with places offering the same benefits, at consumer decision time, is arguably the greatest challenge now faced by destination marketing organisations (DMOs). Since the emergence of the destination branding literature in the late 1990s (see Dosen, Vransevic & Prebezac 1998, Pritchard & Morgan 1998), there has been little reported about issues related to visitor loyalty and destination switching.
Customer relationship management (CRM) has emerged as an important branding tool and strategy within the marketing field (Gronroos, 1994). There are two types of consumer-traveller of interest to DMOs; those who have not previously visited the destination, and those who have. Arguably, most above the line destination advertising appears to fail to distinguish between the two groups. The proposition guiding this paper is that establishing dialogue with selected visitors, in the pursuit of repeat visitation and destination loyalty, is a more efficient and effective use of resources than traditional above the line advertising that targets new customers. CRM is underpinned by the philosophy that stimulating long term relationships with certain customers will be more profitable over time than a never ending series of one-off sales transactions. The cost of reaching new customers by far outweighs the cost of maintaining contact with existing clientele (Kincaid, 2003).
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A recent exploratory study undertaken by one of the authors found there was a general recognition of the potential for visitor relationship management (VRM) by regional tourism organisations in Queensland, Australia (Pike, 2007a). However, none of the RTOs had been able to develop a formal approach towards engagement with previous visitors. The study concluded more research was needed to guide destination marketers about how to initiate meaningful dialogue, at the right time, with the hundreds of thousands of potential repeat visitors to their destination, with whom they do not come into direct contact. Four themes emerged, with the first being the inability of RTOs to track repeat visitation. Following this point it was not surprising therefore that little if any direct communication was undertaken with previous visitors. With the exception of the development of an opt-in online consumer database, RTOs were not explicitly attempting to stay in touch with previous visitors. Third, there was a general assumption that some accommodation operators would be engaging in VRM, even though participants acknowledged VRM had not been topic of discussion in meetings with local industry. Additionally, in a separate survey of consumers in Queensland (Pike, 2006) only 13% of participants could recall receiving promotional material in the previous year from short break destinations they had previously visited. A significant barrier for the RTOs is that visitors’ contact details are only captured by accommodation operators. Thus, there are distinct and substantial differences between the application of CRM by individual businesses and by DMOs, which usually have no direct contact with the visitors they assist in attracting to their destination. It is for this reason the term visitor relationship management (VRM) is considered a more appropriate term for destination marketers than CRM. The aim of the current project was to develop a scale to operationalise visitor relationship orientation of DMOs.
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Literature review The relatively recent shift in thinking towards destinations as brands, particularly since the 1990s, requires a brand management approach focusing on developing relationships with visitors rather than simply focusing on generating sales. The purpose of branding is to evoke emotions and prompt repeat consumer behaviour by way of a promise to the consumer. Recognition of this has led to the development of the concept of consumer-based brand equity (CBBE) as a brand performance measure since the early 1990s (see Aaker 1991, Keller 2003), which offers the potential to provide a link between past marketing efforts and future performance. CBBE has been conceptualised as comprising brand awareness, perceived quality, brand associations and brand loyalty. While there have been many studies of destination awareness, quality and associations in the literature (see for example reviews of the destination image literature by Chon 1990, Echtner and Ritchie 1991, Pike 2002, 2007b, Gallarza, Saura & Garcia 2002), there has been a lack of attention towards destination loyalty (Oppermann 2000, Ritchie & Crouch 2003), which is at the pinnacle of the CBBE hierarchy.
Every successful brand strategy requires effective communication. Not long after the arrival of Aaker’s (1991) seminal branding text was the first integrated marketing communication (IMC) text (see Schultz, Tannenbaum, & Lauterborn, 1993). While there has been little published on the topic in the destination marketing literature IMC has been incorporated in tourism marketing texts (see for example Morrison 2002, Kotler, Bowen & Makens 1999). IMC has been defined as:
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…a cross functional process from creating and nourishing profitable relationships with customers and other stakeholders by strategically controlling or influencing all messages sent to these groups and encouraging data-driven, purposeful dialogue with them (Duncan, 2002).
There are five key fundamentals in this definition, all of which are likely to present significant challenges for destinations. The first is stimulating profitable customer relationships. The second is strengthening stakeholder relationships to enhance understanding of the destination’s brand objectives. The third is creating a crossfunctional process between stakeholders, to ensure brand communication buy-in. The fourth is generating message synergy across different types of media. The fifth is stimulating purposeful dialogue with customers. ‘Purposeful dialogue’ is also at the heart of CRM, about which the first texts also appeared in the early 1990s (see McKenna 1991, Sheth & Parvatiyar 1993).
It is proposed there are two main reasons for DMOs to engage in VRM. The first is the increasing potential for repeat visitation in some market segments. For example, the state tourism organisation for Victoria in Australia reported strong repeat visitation from some of the state’s key markets (see Harris, Jago & King, 2005), such as New Zealand (over 90% repeaters), Singapore (60%) and Japan (10%). Likewise, Tourism Queensland (2006) reported that 93% of New Zealand arrivals were repeat visitors. There are differences in perceptions of destinations between people who have visited a destination before and those who have not visited (Fakeye & Crompton 1991, Milman & Pizam 1995). While many travellers seek new places and new
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experiences, there is evidence to suggest in domestic short break markets, travellers take multiple trips each year and do have favourite destinations (Pike, 2006). The second reason is the extent to which destinations are likely to be substitutable in the face of the sheer number of competing places, particularly for low involvement decisions.
Oppermann (1996, 1997) claimed little had been reported in the tourism literature about repeat visitation. However, in the time since, there has been increasing interest by tourism academics in examining the differences between repeat and first time visitors, particularly relating to: re-visit intentions (see Yuksel 2000, Chen & Gursoy 2001, Niinen, Szivas & Riley 2004, Yoon & Uysal 2005, Alegre & Clader 2006, Huang & Chiu, 2006, Um, Chon & Ro 2006), spending patterns (Alegre & Juaneda, 2006), and trip characteristics (Gitelson & Crompton 1984, Gyte & Phelps 1989, Pyo, Song & Chang 1998, Oppermann 1996, 2000, Lau & McKercher 2004, McKercher & Wong 2004). Research suggests destinations ought to determine whether repeat visitors offer advantages in terms of increased satisfaction, loyalty and therefore yield. Positive indicators would lead to the recognition of the need to engage in dialogue with these visitors.
CRM has been given many different definitions, (see for example Nicholls 2000, Binggelt et al. 2002, Bose 2002, Chang et al. 2002, Chen & Popovich 2003, Boulding et al. 2005, Kamakura et al. 2005, Sigala 2005, Ozgener & Iraz 2006, Stockdale 2007), which generally fit into three distinct categories: i) a business strategy to understand and anticipate consumer needs and wants, ii) a tool to gather customer data over a period of time, and iii) a software program. One of the most commonly
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cited definitions is that proposed by Gronroos (1994, p.9), who suggested the purpose is to “identify and establish, maintain and enhance… relationships with customers…at a profit…by mutual exchange and fulfilment of promises”. It is important to note that in marketing the term ‘relationship’ is a metaphor that is literally false but offers creative possibilities (O’Malley & Tynan, 1999). Marketing relationships are built on knowledge, and when a customer shares information, the marketer should customise the offer (Peppers & Rogers, 2000). CRM is concerned with using customer information and technology to enhance quality experiences in order to maximise loyalty (Kincaid, 2003). It is proposed a VRM orientation involves explicit efforts to develop a long term bond with selected visitors to the destination, in order to stimulate repeat visitation. The aim of this research was to test the development of a scale to operationalize visitor relationship orientation of DMOs.
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Method Since no DMO VRM orientation scale has been developed, a model of CRM orientation was developed from an extensive review of the wider marketing literature, as well as interpretation of a previous qualitative investigation. Initially a total of 42 CRM critical success factors were identified from nine studies (see Bose 2002, Wilson, Daniel & McDonald 2002, Bielski 2003, Beaujean, Davidson & Madge 2006, King & Burgess 2006, Lin, Lin, Huang & Kuo 2006, Ozgener & Iraz 2006, Marchand 2006, Raman, Wittmann & Rauseo 2006). These were then compared to a scale developed to measure CRM orientation in the financial sector (see Sin et al., 2005), which along with a review of the interpretation of a prior qualitative investigation (Pike, 2007a), resulted in the development of a proposed model of DMO VRM orientation. As shown in Figure 1, the model contains 23 items in five dimensions.
(FIGURE 1 ABOUT HERE)
A database of 1435 DMOs was developed as the sample frame. The DMOs comprised CVBs, RTOs, RTBs and STOs in Australia, New Zealand, North America and the United Kingdom, as well as NTOs from around the world. Where possible, specific email contacts were obtained for the marketing/ tourism/ communication management, or chief executive officer/ director positions, otherwise a general enquiries e-mail was obtained. Unfortunately many DMOs provide only general enquiry forms with no contact e-mail addresses, which necessitated the request to participate had to be inserted in this form.
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During August 2008 an invitation to participate in an online survey, hosted by the faculty, was emailed to the 1435 DMOs. One follow-up e-mail was sent in an attempt to increase the response rate, following Sue and Ritter (2007, p. 90). The questionnaire contained two sections. The first asked participants to rate the importance of the 23 CRM items, using a seven point scale anchored at ‘not important’ (1) and ‘very important’ (7). To test the scale properties, the second section asked participants to rate their organisation’s performance across the same 23 items, using a seven point scale. Other questions related to issues of location, structure, and legal entity. An incentive prize draw of 10 copies of a destination marketing text was offered to participants.
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Results A total of 65 completed questionnaires were received, while a further 174 e-mails (12.1%) were returned without reaching the intended participant, for a variety of reasons, such as out of date e-mail addresses and SPAM filters (see Sue & Ritter, 2007). Although the 5.2% usable response rate is considered low, surveys targeting businesses tend to have a lower response than consumer surveys (Sheehan & McMillan, 1999, p. 46, Frazer and Lawley, 2000, p. 74). For example, Boo, Busser and Baloglu’s (2008) online survey of consumers’ perceptions of gambling destinations attracted a 5% response. Additionally, e-mail response rates are typically lower than that for mail surveys due to an increasingly high rate of undeliverable emails (Schaefer & Dillman, 1998, Weible & Wallace, 1998, p. 21). The literature review highlighted the problematic nature of generating large samples of DMOs. For example, Blain, Levy and Ritchie (2005) achieved a sample of 99 DMOs from around the world. Park and Petrick (2006) received only eight responses. They suggested the reasons that DMOs chose not to participate, included nondisclosure policies and uncertainties about how their organisation would progress with the topic being surveyed. These suggestions may help explain the low response rate for this type of study.
Another potential reason for non-response identified in this study was a perception of VRM within DMOs as something not conducted by them, but by visitor centres. For example, a non-participating DMO voiced this concern about the study:
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I have had a look at your survey. In Western Australia it is not the role of DMOs to deal with visitors – it is the role of LTOs local tourist organisations ie visitor centres. In WA no DMOs run VCs so the questionnaire is largely irrelevant.
Another opinion was based around the funding of one New Zealand RTO and the concerns that they faced building and maintaining visitor relationships:
…it impossible to respond to the questions on the basis that as a Regional Marketing Organisation we have neither the mandate nor the funding to be able to even consider undertaking the kind of activities in your questionnaire… The fact is that as an RTO we struggle to maintain our existing funding let alone to secure any increase in funding (we have had the same funding levels for 11 years). Our funders are one Regional Council Community Trust and three District Councils and as we have 3 new Mayors at District Council level none of them really understands why they fund tourism at all. This means that aside from talking to and lobbying Councils, our marketing efforts must be targeted to achieve the best result we possibly can with very limited funds - and the bottom line is visitor nights.
I understand there may be some argument for an RTO to endeavor to maintain visitor relationships; however we have to see this as the responsibility of the tourism operator who is in fact better placed to do so.Perhaps your survey will be easier for a larger and better funded RTO to respond to (our funding is currently around $520,000 pa).
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The sample characteristics are shown in Table 1, where it can be seen that the majority of participants were from North America (51%) and the United Kingdom (28%). Unfortunately, Asia, Africa and South America yielded no responses. In terms of the type of DMO, CVBs were the largest group (46%), followed by RTOs (20%) and TIC/ VICs (20%). Almost half of the participants represented DMOs with staff numbers of 10 employees of less (48%). Only three DMOs had more than 150 staff.
TABLE 1 HERE
A cross-tabulation of employment of a CRM specialist, DMO hierarchy and the number of staff employed, as shown in Table 2 highlights the majority of participants (74%), which were not either an NTO or STO, did not hire a CRM specialist. In comparison, only one of the six NTOs and STOs did not hire a CRM specialist. The grand mean for the importance attribute items is 5.95, which indicates the validity of the items from the perspective of these practitioners. The Cronbach alpha for 23 attribute importance items was .94, which indicates strong reliability for the scale. As shown in Table 3, the means for the 23 attribute performance items range from 6.3 to 4.0. The performance results of the top four attributes indicate the DMOs have a strong visitor orientation. However, the two lowest performance items suggest DMOs struggle to engage in dialogue with previous visitors. As shown in Table 4, the majority (89%) recognised the potential for CRM within their organisation, while almost two thirds indicate communicating with previous visitors. However, less than half are able to track repeat visitation. These results indicate the DMOs’ visitor orientation is generally responsive and reactive rather than proactive.
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(TABLE 2 ABOUT HERE) (TABLE 3 ABOUT HERE) (TABLE 4 ABOUT HERE) Partial least squares (PLS) was used to analyse the data and to test a measurement model of relationship orientation as a second order construct. PLS optimises the explained variance of relationship orientation and supports variance analysis ( R 2 ) and prediction. This is useful for exploratory studies characterised by relatively weak a priori theory and where the primary focus is theory development. Another advantage of PLS is that it supports model types with both reflective and formative constructs and can be used with small samples as is the case with this study (Chin, 1998a, b; 2000; Chin and Gopal, 1995). For PLS analysis, the recommended sample size should be equal ten times either the number of indicators of the most complex formative latent variable or the largest number of independent variables impacting a dependent variable; whichever is greater (Barclay et al. , 1995). Relationship Orientation has five first-order reflective dimensions (i.e. Relationship Commitment, Resources management/allocation, CRM culture, Information generation, Responsiveness) with the most complex dimension, Resources management/allocation, being reflected by seven items. Thus, the dependent variable with the largest number of independent variables impacting it is CRM Organisation. Accordingly, the recommended sample size is would be 70. At 65, the sample size available to us approaches the minimum recommended for PLS analysis. A two stage approach to developing a measure of relationship orientation as a higher order construct was adopted. First, a lower order measurement model of the five dimensions of relationship orientation was estimated. This was followed by the
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estimation of a higher order model of relationship orientation, using aggregated data for each of the first order constructs (factor scores). The reliability and validity of the measures at both levels of abstraction were assessed using a variety of heuristics (factor loadings, average variance extracted, composite reliability).
First order model The average variance extracted, composite reliability, R2 and Cronbach’s α for the five subscales of relationship orientation are reported in Table 5. All of these values exceed their generally accepted recommended minima, and with moderately high R2 values, this suggest that the items reflect the underlying constructs well.
Several tests of discriminant validity were undertaken, these are discussed next and evidence to support discriminant validity is presented. Following this, evidence from three approaches to support the convergent validity of the scale is presented. (TABLE 5 ABOUT HERE) Discriminant validity Evidence of discriminant validity is provided by a low to moderate correlation among measures that are designed to measure conceptually different but related constructs. For example, a phi coefficient significantly less than one offers support for discriminant validity between constructs (Anderson & Gerbing, 1988). The inter-
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factor correlations (φ) are reported in Table 6 and indicate that the scale items discriminate between the dimensions of relationship orientation that they represent. Additional evidence of discriminant validity is provided if the average variance explained by a construct's items is greater than the construct's shared variance with every other construct (i.e. the square of the inter-factor correlations between any two constructs (φ2), Fornell and Larcker 1981). Analysis of the data provides strong evidence of discriminant validity, with the average variance of each Relationship Orientation dimension being greater than its shared variance with any other dimension. It is therefore reasonable to assume all of the first order dimensions of the Relationship Orientation scale to be unidimensional. The inter-factor correlations (φ), squares of the inter-factor correlations (φ2), and average variances extracted are reported in Table 6 also. (TABLE 6 ABOUT HERE) Composite reliability Having established that each of the sub-scales measuring various dimensions of relationship orientation do indeed discriminate between these factors, the next stage in the analysis was to examine composite reliabilities of each of the sub-scales (Gerbing & Anderson 1988, Hair et al. 1998, p. 611) exceed the recommended standards of both Bagozzi and Yi (1991) and Hair et al. (1998), and provide evidence of the internal consistency of the construct indicators. This suggests that the scale items do indeed measure the latent constructs that they purport to.
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Convergent validity Fornell and Larcker (1981) suggest that variance extracted is a stringent test of internal stability and convergent validity. Anderson and Gerbing (1988) offer an alternative heuristic; that significant t-values support the convergent validity of scale items. Both approaches were used to test the convergent validity of the relationship orientation scales. Examining the variances extracted for each of the relationship orientation dimensions, indicates that the scales explain more than 50% of the variance in the data for each of the dimensions and so meet the stringent test of convergent validity set by Fornell and Larcker (1981). Finally, all 23 items load well onto the underlying dimension that they reflect (λ) and have significant t-values >1.96 (Table 7) exceeding Anderson’s and Gerbing’s (1988) heuristic, and suggesting that the scale items adequately represent the dimension that they purport to measure. Overall these tests indicate that the scales measuring the relationship orientation dimensions possess sufficient internal stability and convergent validity to be considered for aggregation to test a higher order model of relationship orientation. (TABLE 7 ABOUT HERE)
Second order model In order to measure the more abstract construct of relationship orientation, the data from each of the scales measuring the dimensions of relationship orientation were aggregated by calculating their factor scores. These aggregate measures were modelled as items reflecting the higher order ‘relationship orientation’ construct.
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In order to test the adequacy of the higher order measurement model a variety of heuristics were examined: item loadings (λ), average variance extracted, composite reliability. The item loadings are reported in Table 8 and, as can be seen in the table, all are high and significant. Other fit statistics also exceed the recommended minima (AVE = 0.71, Composite Reliability = 0.92 and Coefficient α = 0.90) suggesting that aggregating the data to measure the higher order construct is appropriate.
(TABLE 8 ABOUT HERE)
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Conclusion Customer relationship management (CRM) is a business strategy used by organisations to enhance relationships with customers, increase brand loyalty and stimulate repeat purchases. The rationale for CRM is that engaging in dialogue with existing customers can represent a more efficient use of resources than above the line advertising to attract a continual stream of non-customers. This study examines the CRM orientation of destination marketing organisations (DMOs), since there has been a lack of published research in this area. Motivating this research was an exploratory study of 11 Queensland RTOs , which found that while management recognised the potential of CRM, implementation was problematic. The aim of the study was to test a scale to operationalise visitor relationship orientation of DMOs.
A model of visitor relationship orientation, comprising 23 items in five dimensions was developed through a literature review as well as interpretation of a prior qualitative investigation. The items were similar to a model of CRM orientation in the financial sector developed by Sin, Tse and Yim (2005). An online questionnaire was sent to a sample frame of 1,435 DMOs around the world, consisting of national tourism organisations, state tourism organisations and regional tourism organisations. A usable response rate of 5.2% (65 participants) was obtained. Due to the small sample size the PLS method of structural equation modelling was used to examine the data. The data fit the proposed model well.
One of the key issues to emerge from the study was the small response rate from a sample frame of 1435 DMOs. Even though incentives were offered, and a follow up request to participate was made, the study failed to attract a large and representative
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sample. As discussed the problem is not unique to this project, with previous studies also failing to attract a sample of DMOs that would enable generalisation of findings. Given that i) the majority of tourism activities take place at destinations, ii) destinations are the biggest brands in tourism, and iii) there is a lack of published research about visitor relationship management by DMOs, there is clearly a need for a different approach to sampling. At a global level, perhaps the solution lies with a coordinated approach in conjunction with the UNWTO, and at national and state levels through NTOs and STOs.
While the sample characteristics do not permit generalising, the findings did support the interpretation of a previous qualitative investigation of visitor relationship orientation of RTOs in Queensland, Australia. The results of this study indicate the DMOs’ visitor orientation is generally responsive and reactive rather than proactive. That is, DMOs are in general able to respond to visitor enquiries in an efficient and effective manner, but fail to be able to proactively engage in dialogue with previous visitors. Comments from a New Zealand RTO suggest that DMOs remain focussed on attracting visitors rather than encouraging repeat visits. The RTO stated: our marketing efforts must be targeted to achieve the best result we possibly can with very limited funds - and the bottom line is visitor nights. This appears to suggest that the lack of funding and the focus on recruiting new visitors hinders the development of a relationship orientation and that tactics remain focused on a more transactional approach to marketing. DMOs rarely come into direct contact with the visitors they have been successful in attracting to their destination. The DMO doesn’t therefore have access to the contact details of these consumers, who stay in commercial accommodation or with friends and relatives. Without access to such contact details,
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the development of a database is problematic for the DMO. Such a database underpins any form of continued contact with previous visitors. Therefore more research is required to identify i) how DMOs are able to develop a database of previous visitors, and then ii) how DMOs can engage in meaningful dialogue. The latter involves engaging with previous visitors at an individual or segment level, where offers are tailored to specific needs at relevant times. This is clearly more than an e-newsletter emailed to all database contacts.
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Figure 1 – Proposed model of DMO VRM orientation CRM culture Visitor relationship orientation Information generation CRM culture Having effective interdepartmental communication. An organisational structure that is designed around visitors.
Resources
Top management supporting the acquisition and deepening of visitor relationships.
management
Assessing whether visitors feel services should be modified.
Information generation Providing ongoing, two-way communication with key visitors.
Responsiveness
Making an effort to find out what key visitor needs are. Providing customised services to key visitors. Understanding the needs of key visitors. Maintaining a comprehensive database of visitors.
Relationship commitment
Resources management Employee training to help acquire and deepen visitor relationships. The right personnel for the technology used to build visitor relationships. Having the right hardware to serve visitors. Having the right software to serve visitors. The sales and marketing expertise and resources to manage visitor relationships. Establishing and monitoring performance standards relative to visitors. Working with key visitors to customise the destination’s offerings.
Responsiveness
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Responding to visitor requests promptly. Prompt service from employees of the organisation. Employees being willing to help visitors in a responsive manner. Treating all key visitors with great care.
Relationship commitment Having clear goals for visitor acquisition and retention Committing time and resources to managing relationships with visitors. Having individual visitor information available.
Table 1 – Sample characteristics n Organisation Location
Type of DMO
Valid Percent
North America
33
50.8
United Kingdom
18
27.7
New Zealand
8
12.3
Europe
3
4.6
Australia
2
3.1
Asia
0
0
Africa
0
0
Central/ South America
0
0
Other
1
1.5
Total
65
100
CVB
30
46.2
RTO
13
20.0
TIC/ VIC
13
20.0
NTO
5
7.7
STO
1
1.5
30
Number of Staff
CRM Specialist
Other
3
4.6
Total
65
Less than 10
31
48.4
11-20
16
25.0
21-30
6
9.4
31-40
4
6.2
51-100
2
3.1
41-50
1
1.6
101-150
1
1.6
More than 150
3
4.7
100
Total (One missing)
64
100
No CRM specialist
48
23.1
Full-time CRM specialist
15
3.1
Part-time CRM specialist
2
73.8
Total
65
100
31
Table 2 - Cross Tabulation of DMO characteristics Hierarchy
Hierarchy
(NTOs/STOs) (All others)
No. of Staff No. of (
